A note on the probability distribution function of the surface electromyogram signal

AbstractThe probability density function (PDF) of the surface electromyogram (EMG) signals has been modelled with Gaussian and Laplacian distribution functions. However, a general consensus upon the PDF of the EMG signals is yet to be reached, because not only are there several biological factors that can influence this distribution function, but also different analysis techniques can lead to contradicting results. Here, we recorded the EMG signal at different isometric muscle contraction levels and characterised the probability distribution of the surface EMG signal with two statistical measures: bicoherence and kurtosis. Bicoherence analysis did not help to infer the PDF of measured EMG signals. In contrast, with kurtosis analysis we demonstrated that the EMG PDF at isometric, non-fatiguing, low contraction levels is super-Gaussian. Moreover, kurtosis analysis showed that as the contraction force increases the surface EMG PDF tends to a Gaussian distribution

Event Stream Processing with Multiple Threads

Current runtime verification tools seldom make use of multi-threading to speed up the evaluation of a property on a large event trace. In this paper, we present an extension to the BeepBeep 3 event stream engine that allows the use of multiple threads during the evaluation of a query. Various parallelization strategies are presented and described on simple examples. The implementation of these strategies is then evaluated empirically on a sample of problems. Compared to the previous, single-threaded version of the BeepBeep engine, the allocation of just a few threads to specific portions of a query provides dramatic improvement in terms of running time

Multi-Objective Optimization of Demand Side Management and Multi DG in the Distribution System with Demand Response

The optimal management of distributed generation (DG) enhances the efficiency of the distribution system; On the other hand, increasing the interest of customers in optimizing their consumption improves the performance of DG. This act is called demand side management. In this study, a new method based on the intelligent algorithm is proposed to optimal operate the demand side management in the presence of DG units and demand response. Firstly, the best location and capacity of different technologies of DG are selected by optimizing the technical index including the active and reactive loss and the voltage profile. Secondly, the daily performance of multi-DG and grid is optimized with and without considering the demand response. The economic and environmental indices are optimized in this step. In both steps, the non-dominated sorting firefly algorithm is utilized to multi-objective optimize the objective functions and then the fuzzy decision-making method is used to select the best result from the Pareto optimal solutions. Finally, the proposed method is implemented on the IEEE 33-bus distribution system and actual 101-bus distribution systems in Khoy-Iran. The obtained numerical results indicate the impact of the proposed method on improving the technical, economic and environmental indices of the distribution system

Multiview classification and dimensionality reduction of scalp and intracranial EEG data through tensor factorisation

Electroencephalography (EEG) signals arise as a mixture of various neural processes that occur in different spatial, frequency and temporal locations. In classification paradigms, algorithms are developed that can distinguish between these processes. In this work, we apply tensor factorisation to a set of EEG data from a group of epileptic patients and factorise the data into three modes; space, time and frequency with each mode containing a number of components or signatures. We train separate classifiers on various feature sets corresponding to complementary combinations of those modes and components and test the classification accuracy of each set. The relative influence on the classification accuracy of the respective spatial, temporal or frequency signatures can then be analysed and useful interpretations can be made. Additionaly, we show that through tensor factorisation we can perform dimensionality reduction by evaluating the classification performance with regards to the number mode components and by rejecting components with insignificant contribution to the classification accuracy

Co-creation facilitates translational research on upper limb prosthetics

People who either use an upper limb prosthesis and/or have used services provided by a prosthetic rehabilitation centre, hereafter called users, are yet to benefit from the fast-paced growth in academic knowledge within the field of upper limb prosthetics. Crucially over the past decade, research has acknowledged the limitations of conducting laboratory-based studies for clinical translation. This has led to an increase, albeit rather small, in trials that gather real-world user data. Multi-stakeholder collaboration is critical within such trials, especially between researchers, users, and clinicians, as well as policy makers, charity representatives, and industry specialists. This paper presents a co-creation model that enables researchers to collaborate with multiple stakeholders, including users, throughout the duration of a study. This approach can lead to a transition in defining the roles of stakeholders, such as users, from participants to co-researchers. This presents a scenario whereby the boundaries between research and participation become blurred and ethical considerations may become complex. However, the time and resources that are required to conduct co-creation within academia can lead to greater impact and benefit the people that the research aims to serve

Evidence for sparse synergies in grasping actions

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) – sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) – sparsity in synergy representation – i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) – a novel view combining both SC and SE – i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks

Comparison of therapeutic effects of Fennelin and Mefenamic Acid on Primary Dysmenorrhea.

AbstractBackground and Purpose: Dysmenorrhea is one the most common disorders in Gynecology, which occurs in 50% of women with regular menstrual cycls. There have been various treatment methods regarding this, among which the drugs with less side effects are preferred. The porpuse of the present study, is to compare the effect of Fennelin and Mefenamic Acid on primary dysmenorrhea.Materials and Methods: This research is the result of an experimental study at the level of a double-blind clinical trial in 2006. In this study, 104 students with moderate to severe primary dysmenorrhea were randomly selected and assigned into 3 drug-taking groups, including Fennelin (36), Mefenamic Acid(36) and Placebo(32). They were assigned to receive the relevant drugs in two successive menstrual cycles at the beginning of the pain. The selected subjects were asked to fill out the questionnaires regarding the severity of pain, hemorrhage and clinical problems in the first visit, during the first five hours, 48 hours and the first three days in two successive cycles.Results: There were no significant differences between the 3 selected groups regarding the age and the characteristics of menstruation. The average age of the subjects was 20.7 ± 0.16 and the average age of the beginning of primary dysmenorrhea was 15.11± 0.26. 71.2 % of subjects had moderate while 28.8 % with severe dysmenorrhea. The pain severity highly decreased in Fennelin takers compared with the Placebo takers, and as the time of treatment continued, this difference increased. However, there was no significant difference between the Fennelin and Mefenamic Acid takers. The effect of Fennelin was also more than Mefenamic Acid in reducing the severity of hemorrhage. There was no significant difference between the 3 groups regarding the clinical symptoms, but there was considerable reduction in the severity of clinical problems in Fennelin takers compared with the two other groups. According to the drug-takers, Fennelin was more effective in reducing the complaints compared with Placebo; however, it had no significant difference from Mefenamic Acid.Conclusion: The effect of Fennelin in relieving primary dysmenorrhea is not less than Mefenamic Acid, and it can be useful in reducing the severity of pain, hemorrhage and clinical symptoms. Therefore, due to the safety of herbal drugs, it can replace the chemical drugs